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Georgetown University

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Detailed Course Information

 

Fall 2017
Sep 20, 2017
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Information Select the desired Level or Schedule Type to find available classes for the course.

BIST 532 - Machine Learning for Bioinform
This course is a combination of theories and empirical skills on managing, processing and analyzing high-throughput biomedical data generated from a variety of "Omics" technologies, which spans genomics, trascriptomics, proteomics, and metabolomics. It introduces the students to the conceptual and experimental background, together with specific guidelines for handling raw data. Hand-on skills with R/Bioconductor and other software tools will be covered on popular "Omics" applications, such as microarray gene expression profiling, mass spectrometry-based metabolomics, RNA-seq, pathway analysis, and etc.

3.000 Credit hours
3.000 Lecture hours

Levels: MN or MC Graduate
Schedule Types: Lecture

Biostatistics & Epidemiology Department

Restrictions:
Must be enrolled in one of the following Majors:     
      Biostatistics
      Biostatistics
      Epidemiology

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